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Trends Cogn Sci. 2010 Jul;14(7):293-300. doi: 10.1016/j.tics.2010.05.001. Epub 2010 Jun 11.

What to believe: Bayesian methods for data analysis.

Author information

1
Department of Psychological and Brain Sciences, Indiana University, 1101 E. 10th St., Bloomington, IN 47405-7007, USA. kruschke@indiana.edu

Abstract

Although Bayesian models of mind have attracted great interest from cognitive scientists, Bayesian methods for data analysis have not. This article reviews several advantages of Bayesian data analysis over traditional null-hypothesis significance testing. Bayesian methods provide tremendous flexibility for data analytic models and yield rich information about parameters that can be used cumulatively across progressive experiments. Because Bayesian statistical methods can be applied to any data, regardless of the type of cognitive model (Bayesian or otherwise) that motivated the data collection, Bayesian methods for data analysis will continue to be appropriate even if Bayesian models of mind lose their appeal.

PMID:
20542462
DOI:
10.1016/j.tics.2010.05.001
[Indexed for MEDLINE]

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